{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6.1　坐标轴概述"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('left', <matplotlib.spines.Spine object at 0x0000000010CB0640>), ('right', <matplotlib.spines.Spine object at 0x0000000010CB07C0>), ('bottom', <matplotlib.spines.Spine object at 0x0000000010CB0970>), ('top', <matplotlib.spines.Spine object at 0x0000000010CB0A90>)])\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "cur_ax = plt.gca()\n",
    "print(cur_ax.spines)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6.2　向任意位置添加坐标轴"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAR4AAACSCAYAAACTzKXBAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAALzElEQVR4nO3da4xcdR3G8e9DW8DYVhO2Kmm7LImNt0SDLlVTYyBGo1AlRpTGiGBMGokkRUuM4OWFiS+MCRG81RowXjB4AbUxKFalAhqR3UIhbZXWKmlLQ61a2kasmc3PF3Mkx9mZ7mxnzv9c5vkkTWfOnM75zYt59pn/nO5RRGBmltIZZQ9gZqPHwWNmyTl4zCw5B4+ZJefgMbPkHDxmltzCIp50bGwsJiYminhqq4np6ekjEbGs7DmsmgoJnomJCaampop4aqsJSU+UPYNVlz9q2Wk72Zrht3uPlD2G1ZCDx07LoweO8vYvPsBVt/2Bg0efKXscq5lCPmpZc51szXDLr/aw6Tf7WLb4LL7+/kmWP/85ZY9lNePgsb49euAo1/9gB48/dYJ3v2YFn1z7cp73nEVlj2U15OCxOXW2nG9cfSEXv/QFZY9lNebgsVNyy7EiOHisK7ccK5KDx2Zxy7GiOXjsWW45loqDxwC3HEvLwTPi3HKsDA6eEeaWY2Vx8Iwgtxwrm4NnxLjlWBU4eEaEW45ViYNnBLjlWNU4eBrMLceqysHTUG45VmV9B4+kBcAUcDAi1hY3kg3CLcfqYD6NZwOwG1ha0Cw2ILccq4u+gkfSCuBS4LPARwudyObNLcfqpt/G8wXgY8CSXjtIWg+sBxgfHx94MOvPjv3tlrPn8Akuf80KPuWWYzUwZ/BIWgscjohpSRf12i8iNgObASYnJ2NYA1p3J1sz3PzLPXztvn2MLT7TLcdqpZ/GswZ4h6RLgLOBpZK+ExHvK3Y068Utx+puzuCJiBuAGwCyxnO9Q6ccbjnWFD6PpybccqxJ5hU8EbEN2FbIJNaVW441kRtPhbnlWFM5eCrILceazsFTMW45NgocPBXhlmOjxMFTAW45NmocPCVyy7FR5eApiVuOjTIHT2JuOWYOnqTccszaHDwJuOWY/T8HT8Hccsxmc/AUxC3HrDcHTwHccsxOzcEzRG45Zv1x8AyJW45Z/xw8A3LLMZs/B88A3HLMTo+D5zS45ZgNxsEzT245ZoNz8PQp33J8tU6zwTh4+pBvOb4mudngHDyn4JZjVgwHTw9uOWbFcfB0cMsxK56DJ8ctxywNBw9uOWapjXzwuOWYpTeyweOWU0+S/gocB2aAVkRMdjwu4GbgEuBfwNURsT31nHZqIxk8bjm1d3FEHOnx2NuAVdmf1wJfzf7uaWxsLCYmJoY6oLVNT08fiYhlndtHKnhmtZwPXMjFL3HLaZjLgG9FRAC/l/R8SedGxKFe/2BiYoKpqal0EzbUydYMAGctXPDsNklPdNv3jLmeTNJKSfdK2iVpp6QNwxo0pR37j7L2lgf4yrY/865XL+eej7zRoVNPAfxC0rSk9V0eXw7sz90/kG2zAv3v/XXT1sf72r+fxtMCNkbEdklLgGlJWyNi1yCDpuKW0zhviIiDkl4AbJX0x4i4b75PkoXWeoDx8fFhzzgyOt9frzv/nL7+3ZzBk1XUQ9nt45J20/4JUvngefRAey3n8adO8J7JFXziUq/l1F1EHMz+PizpR8BqIB88B4GVufsrsm2dz7MZ2AwwOTkZhQ3cYIOslc5rjUfSBHAB8GCXxyrzE8Qtp5kkPRc4I/sB+FzgLcBnOnbbAlwr6Q7ai8pPn2p9x+ZvGN8I9x08khYDdwLXRcSxzser8hMkn8JuOY3zQuBH7W/MWQh8NyJ+LulDABGxCbib9lfpe2l/nf6BkmZtpGF9I9xX8EhaRDt0bo+Iu+Z9lATccpovIvYBr+qyfVPudgAfTjnXKBj2eW9zBk92QtatwO6IuOm0j1Qgtxyz4hRx3ls/jWcNcCXwmKRHsm03RsTdAx15CNxyzIpzsjXDLb/aw6bfDP/s/n6+1XoA0FCONkRuOWbFyX8jXMTZ/bU7c9ktx6w4RbacvFoFj1uOWXGKbjl5tQgetxyz4qRqOXmVDx63HLPipGw5eZUNHrccs+KU0XLyKhk8/n05ZsUpq+XkVSp4/FsBzYpTdsvJq0zwuOWYFacKLSev9OBxyzErTpVaTl6pweOWY1acqrWcvFKCxy3HrDhVbTl5yYPHLcesOFVuOXnJgsctx6w4dWg5eUmCZ9eTx9hwx8NuOWYFqEvLyUsSPBL8uzVT+RQ2q5O6tZy8JMHzsnOXcu/Gi1i4YM7LeJlZH+rYcvKSrfE4dMwGV+eWk1f6CYRm1p+6t5y8QoJnenr6SJdrJo8BR4o4XgX5tcJ5qQdpqnzLGVt8Zm1bTl4hwRMRyzq3SZqKiMkijlc1fq02LE1qOXn+qGVWQU1Zy+nFwWO1IWkl8C3aVxQNYHNE3Nyxz0XAT4C/ZJvuiojOyxxXWlNbTl7K4Nmc8Fhl82stRgvYGBHbJS0BpiVtjYhdHfvdHxFrE841FE1vOXnJgie7tvpI8Gst7FiHgEPZ7eOSdgPLgc7gqZ1RaDl5/qhltSRpArgAeLDLw6+XtAN4Erg+InamnG0+Rqnl5Dl4rHYkLQbuBK6LiGMdD28HzouIE5IuAX4MrOryHOuB9QDj4+PFDtzDqLWcvCSnE0t6q6Q/Sdor6eMpjlkGSSsl3Stpl6SdkjaUPVPRJC2Q9LCknyY63iLaoXN7RNzV+XhEHIuIE9ntu4FFksa67Lc5IiYjYnLZsllnfxTqZGuGz9/zR975ld9x7JkW37j6Qj7/7leNTOhAgsYjaQHwZeDNwAHgIUlbuiwINkG/i59NsgHYDSwt+kCSBNwK7I6Im3rs8yLgqYgISatp/3D9e9Gz9WuUW05eio9aq4G9EbEPQNIdwGU0YEGwU5MXP7uRtAK4FPgs8NEEh1wDXAk8JumRbNuNwDhARGwCLgeukdQCngHWRUQkmO2URnUtp5cUwbMc2J+7fwB4bYLjlmqOxc+m+ALwMWBJioNFxAOA5tjnS8CXUszTL7ec2by4XIA5Fj8bQdJa4HBETGcn7VkHt5zeUgTPQWBl7v6KbFsjzbX42SBrgHdk3xydDSyV9J2IeF/Jc1WCW86ppQieh4BVks6nHTjrgPcmOG5y/Sx+NkVE3ADcAM/+N4XrHTpuOf0qPHgioiXpWuAeYAFwW5VP6BpQ18XP7Gtdazi3nP4lWePJ3niNf/P1s/jZRBGxDdhW8hilccuZPy8umw3ALef0OHjMToNbzmAcPGbz5JYzOAePWZ/ccobHwWPWB7ec4XLwmJ3CydYMN/9yD1+7zy1nmBw8Zj3s2N9uOXsOu+UMm4PHrINbTvEcPGY5jx44ysbvu+UUzcFjlrPryWMc/3fLLadgDh6znCsuXMmlrzyXJWe75RQpye9cNqsLSQ6dBFSB3wppVipJfwOeyG0aA46UNM6wVOU1nBcRs36bvoPHrIOkqYiYLHuOQVT9Nfijlpkl5+Axs+QcPGazJbsefIEq/Rq8xmNmybnxmFlyDh4bWZLeKulPkvZK+niXx8+S9L3s8QezizRWhqSVku6VtEvSTkkbuuxzkaSnJT2S/fl0GbN28pnLNpIkLQC+DLyZ9tVtH5K0peM69x8E/hkRL5a0DvgccEX6aXtqARsjYrukJcC0pK0drwHg/ohYW8J8Pbnx2KhaDeyNiH0R8R/gDuCyjn0uA76Z3f4h8Kbs2mmVEBGHImJ7dvs4sJv2JcMrz8Fjo2o5sD93/wCz37TP7hMRLeBp4Jwk081T9jHwAuDBLg+/XtIOST+T9Iq0k3Xnj1pmNSdpMe3LZl8XEcc6Ht5O+78tnMguN/1jYFXiEWdx47FRdRBYmbu/ItvWdR9JC4HnAX9PMl2fJC2iHTq3R8RdnY9HxLGIOJHdvhtYJGks8ZizOHhsVD0ErJJ0vqQzgXXAlo59tgBXZbcvB34dFTrxLVtvuhXYHRE39djnRf9bl5K0mvZ7vvTw9EctG0kR0ZJ0LXAPsAC4LSJ2SvoMMBURW2i/qb8taS/wD9rhVCVrgCuBxyQ9km27ERgHiIhNtAPzGkkt4BlgXRXC02cum1ly/qhlZsk5eMwsOQePmSXn4DGz5Bw8Zpacg8fMknPwmFlyDh4zS+6/JVdjKrkzTA4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "ax = plt.axes((0.2, 0.5, 0.3, 0.3))\n",
    "ax.plot([1, 2, 3, 4, 5])\n",
    "ax2 = plt.axes((0.6, 0.4, 0.2, 0.2))\n",
    "ax2.plot([1, 2, 3, 4, 5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6.3　定制刻度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.3.1　定制刻度的位置和格式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "from matplotlib.dates import DateFormatter, HourLocator\n",
    "ax = plt.gca()\n",
    "hour_loc = HourLocator(interval=2)\n",
    "date_fmt = DateFormatter('%Y/%m/%d')\n",
    "ax.xaxis.set_major_locator(hour_loc)\n",
    "ax.xaxis.set_major_formatter(date_fmt)\n",
    "plt.tick_params(labelrotation=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.3.2　定制刻度的样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.tick_params(direction='out', length=6, width=2, colors='r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.3.3　实例1：深圳市24小时的平均风速"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 01_average_wind_speed_in_shenzhen\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.dates import DateFormatter, HourLocator\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "dates = ['201910240','2019102402','2019102404','2019102406',\n",
    "         '2019102408','2019102410','2019102412', '2019102414',\n",
    "         '2019102416','2019102418','2019102420','2019102422','201910250' ]\n",
    "x_date = [datetime.strptime(d, '%Y%m%d%H') for d in dates]\n",
    "y_data = np.array([7, 9, 11, 14, 8, 15, 22, 11, 10, 11, 11, 13,  8])\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes((0.0, 0.0, 1.0, 1.0))\n",
    "ax.plot(x_date, y_data, '->', ms=8, mfc='#FF9900')\n",
    "ax.set_title(' 深圳市24小时的平均风速')\n",
    "ax.set_xlabel('时间（h）')\n",
    "ax.set_ylabel('平均风速(km/h)')\n",
    "# 设置 x 轴主刻度的位置和格式\n",
    "date_fmt = DateFormatter('%H:%M')\n",
    "ax.xaxis.set_major_formatter(date_fmt)\n",
    "ax.xaxis.set_major_locator(HourLocator(interval=2))\n",
    "ax.tick_params(direction='in', length=6, width=2, labelsize=12)\n",
    "ax.xaxis.set_tick_params(labelrotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6.4　隐藏轴脊"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.4.1　隐藏全部轴脊"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpathes\n",
    "polygon = mpathes.RegularPolygon((0.5, 0.5), 6, 0.2, color='g')\n",
    "ax = plt.axes((0.3, 0.3, 0.5, 0.5))\n",
    "ax.add_patch(polygon)\n",
    "# 隐藏全部轴脊\n",
    "ax.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.4.2　隐藏部分轴脊"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpathes\n",
    "xy = np.array([0.5,0.5])\n",
    "polygon = mpathes.RegularPolygon(xy, 5, 0.2,color='y')\n",
    "ax = plt.axes((0.3, 0.3, 0.5, 0.5))\n",
    "ax.add_patch(polygon)\n",
    "# 依次隐藏上轴脊、左轴脊和右轴脊\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.spines['left'].set_color('none')\n",
    "ax.spines['right'].set_color('none')\n",
    "# 插入如下代码\n",
    "# ax.yaxis.set_ticks_position('none')\n",
    "# ax.set_yticklabels([])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.4.3　实例2：深圳市24小时的平均风速（隐藏部分轴脊）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 02_average_wind_speed_in_shenzhen(2)\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.dates import DateFormatter, HourLocator\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "dates = ['201910240','2019102402','2019102404','2019102406',\n",
    "         '2019102408','2019102410','2019102412', '2019102414',\n",
    "         '2019102416','2019102418','2019102420','2019102422','201910250' ]\n",
    "x_date = [datetime.strptime(d, '%Y%m%d%H') for d in dates]\n",
    "y_data = np.array([7, 9, 11, 14, 8, 15, 22, 11, 10, 11, 11, 13,  8])\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes((0.0, 0.0, 1.0, 1.0))\n",
    "ax.plot(x_date, y_data, '->', ms=8, mfc='#FF9900')\n",
    "ax.set_title('深圳市24小时的平均风速')\n",
    "ax.set_xlabel('时间（h）')\n",
    "ax.set_ylabel('平均风速(km/h)')\n",
    "date_fmt = DateFormatter('%H:%M')\n",
    "ax.xaxis.set_major_formatter(date_fmt)\n",
    "ax.xaxis.set_major_locator(HourLocator(interval=2))\n",
    "ax.tick_params(direction='in', length=6, width=2, labelsize=12)\n",
    "ax.xaxis.set_tick_params(labelrotation=45)\n",
    "# 隐藏上轴脊和右轴脊\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.spines['right'].set_color('none')\n",
    "plt.show()    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6.5　移动轴脊"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.5.1　移动轴脊的位置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpathes\n",
    "xy = np.array([0.5,0.5])\n",
    "polygon = mpathes.RegularPolygon(xy, 5, 0.2,color='y')\n",
    "ax = plt.axes((0.3, 0.3, 0.5, 0.5))\n",
    "ax.add_patch(polygon)\n",
    "# 隐藏上轴脊和右轴脊\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.spines['right'].set_color('none')\n",
    "# 移动轴脊的位置\n",
    "ax.spines['left'].set_position(('data', 0.5))\n",
    "ax.spines['bottom'].set_position(('data', 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.5.2　实例3：正弦与余弦曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 03_sin_and_cos\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "x_data = np.linspace(-2 * np.pi, 2 * np.pi, 100)\n",
    "y_one = np.sin(x_data)\n",
    "y_two = np.cos(x_data)\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes((0.2, 0.2, 0.7, 0.7)) \n",
    "ax.plot(x_data, y_one, label='正弦曲线 ')\n",
    "ax.plot(x_data, y_two, label='余弦曲线 ')\n",
    "ax.legend()\n",
    "ax.set_xlim(-2 * np.pi, 2 * np.pi)\n",
    "ax.set_xticks([-2  * np.pi, -3 * np.pi / 2, -1 * np.pi, -1 * np.pi / 2, \n",
    "               0, np.pi / 2, np.pi, 3  * np.pi / 2, 2  * np.pi])\n",
    "ax.set_xticklabels(['$-2\\pi$', '$-3\\pi/2$', '$-\\pi$', '$-\\pi/2$ ', '$0$', \n",
    "                    '$\\pi/2$', '$\\pi$', '$3\\pi/2$', '$2\\pi$'])\n",
    "ax.set_yticks([-1.0, -0.5, 0.0, 0.5, 1.0])\n",
    "ax.set_yticklabels([-1.0, -0.5, 0.0, 0.5, 1.0])\n",
    "# 隐藏右轴脊和上轴脊\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "# 移动左轴脊和下轴脊的位置\n",
    "ax.spines['left'].set_position(('data', 0))\n",
    "ax.spines['bottom'].set_position(('data', 0))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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